






"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__SCREAMING_SNAKE_CASE   =   logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE   =   {
    'microsoft/resnet-50': 'https://huggingface.co/microsoft/resnet-50/blob/main/config.json',
}




class 						__UpperCamelCase     (     UpperCamelCase   ,     UpperCamelCase						):
					lowercase_    :				List[str]      =  """resnet"""
					lowercase_    :				Optional[int]      =  ["""basic""", """bottleneck"""]
					def __init__(							self							:	Dict     , UpperCAmelCase							:	Optional[Any]=3     , UpperCAmelCase							:	int=64     , UpperCAmelCase							:	Union[str, Any]=[256, 512, 1024, 2048]     , UpperCAmelCase							:	Optional[int]=[3, 4, 6, 3]     , UpperCAmelCase							:	Dict="bottleneck"     , UpperCAmelCase							:	int="relu"     , UpperCAmelCase							:	Any=False     , UpperCAmelCase							:	Tuple=None     , UpperCAmelCase							:	int=None     , **UpperCAmelCase							:	Dict     , )	->       str:
											super().__init__(**UpperCAmelCase   )
											if layer_type not in self.layer_types:
																	raise ValueError(f"""layer_type={layer_type} is not one of {",".join(self.layer_types   )}"""   )
											lowerCAmelCase   :List[str]						=			num_channels
											lowerCAmelCase   :List[Any]						=			embedding_size
											lowerCAmelCase   :List[str]						=			hidden_sizes
											lowerCAmelCase   :Any						=			depths
											lowerCAmelCase   :Union[str, Any]						=			layer_type
											lowerCAmelCase   :Optional[Any]						=			hidden_act
											lowerCAmelCase   :Optional[Any]						=			downsample_in_first_stage
											lowerCAmelCase   :Tuple						=			['stem'] + [f"""stage{idx}""" for idx in range(1     , len(UpperCAmelCase   ) + 1   )]
											lowerCAmelCase	, lowerCAmelCase   :Tuple						=			get_aligned_output_features_output_indices(
											    out_features=UpperCAmelCase     , out_indices=UpperCAmelCase     , stage_names=self.stage_names   )




class 						__UpperCamelCase     (     UpperCamelCase						):
					lowercase_    :				Tuple      =  version.parse("""1.11"""						)
					@property
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       Mapping[str, Mapping[int, str]]:
											return OrderedDict(
											    [
											        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
											    ]   )
					@property
					def        UpperCAmelCase__ (							self							:	int   )	->       float:
											return 1e-3







"""simple docstring"""


def        UpperCAmelCase      (					a__     ,      a__ ):





						'''simple docstring'''






						lowerCAmelCase   :Tuple						=			len(a__ )
						print('The following activities are selected:' )

						# The first activity is always selected
						lowerCAmelCase   :Dict						=			0
						print(a__     ,      end=',' )

						# Consider rest of the activities
						for j in range(a__ ):
												# If this activity has start time greater than
												# or equal to the finish time of previously
												# selected activity, then select it
												if start[j] >= finish[i]:
																		print(a__     ,      end=',' )
																		lowerCAmelCase   :List[str]						=			j


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		__SCREAMING_SNAKE_CASE   =   [1, 3, 0, 5, 8, 5]
		__SCREAMING_SNAKE_CASE   =   [2, 4, 6, 7, 9, 9]
		print_max_activities(start, finish)